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In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is?

In SVMs (Support vector machines) Data points are log-transformed and normalized as in method A, where for N observations of a gene i, the log transform Xi of the expression level Ei and reference level Ri is? Correct Answer Xi = \(\frac{Log (E_i/R_i)}{\sqrt{\sum_{j=1,N} Log_{z-2} (E_j/R_j)}}\)

SVMs were used to categorize genes based on 79 different sets of data points from studies of the yeast cell cycle and are particularly useful for such complex data sets. Gene combinations averaged over all experimental conditions are then examined by a multidimensional analysis.

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How does number of observations influence overfitting? Choose the correct answer(s).Note: Rest all parameters are same
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2. In case of fewer observations, it is hard to overfit the data.
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4. In case of more observations, it is hard to overfit the data.
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